Requirements: English
Company: Experis
Region: Hesperange , Luxembourg
Experis IT Luxembourg is actively looking for a Senior AI, BI and Data Analytics Solutions Engineer (m/f) for one of its clients in Luxembourg.
Your responsibilities
- Develop prototypes and data-centric solutions for various users using Data Analytics (DA) and Artificial Intelligence (AI).
- Provide guidance, support, and training for AI and DA tasks for both technical and non-technical audiences (Modeling, Design, Architectural Reviews, AI initiatives, Standards, and Processes, Center of Expertise).
- Prepare architectural outputs related to AI and DA (Reference Data Architecture, Data Platforms).
- Collect and analyze business requirements.
- Perform technical analyses and create specifications for AI and DA solutions.
- Conduct exploratory data analyses to identify, interpret, and analyze patterns and trends in complex datasets for diagnosis and prediction.
- Design, model, develop, manage, and review end-to-end DA and AI products, prototypes, and proof of concepts on both on-premise and cloud data platforms, including data preparation, feature engineering, model selection and training, visualization, deployment, monitoring, and maintenance.
- Implement MLOps practices, including automated testing and quality assurance.
- Define and document training and support procedures.
- Maintain DA and AI products, including troubleshooting, bug fixing, performance analysis, and technical migrations.
- Architect, design, deploy, and manage components of data platforms.
- Integrate and reuse COTS, SaaS, PaaS, and SaaS solutions.
- Design and implement data protection and security measures.
- Define testing strategies, design tests, and conduct testing.
- Establish best practices and standards.
- Conduct technology watch, evaluate technologies, and contribute to platform definition and strategy documents.
Your profile
- Bachelor''s degree in Computer Science, Information Technology, or any related field.
- Business analysis skills.
- Strong analytical skills, capable of identifying patterns and gaps while exploring data.
- Deep knowledge of statistical analysis and data-driven decision-making.
- Extensive experience with Data Science and AI techniques, particularly in prediction, machine learning, and Generative AI.
- Proficient in programming languages for data analytics and AI (e.g., Python, R) and frameworks (e.g., .NET AI, SpringAI).
- Experienced in machine learning algorithms (e.g., ANN, random forest) and deep learning frameworks.
- Skilled in developing reusable AI models (e.g., huggingface) and Generative AI APIs (e.g., OpenAI).
- Experienced in the industrialization of DA and AI solutions.
- Knowledgeable about MLOps tools, testing, and quality assurance.
- Proficient with visualization tools (e.g., PowerBI).
- Knowledgeable in SQL (e.g., Oracle, SQL Server) and No-SQL databases (e.g., MongoDB, Neo4j).